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DATA-X: m130 - Introduction to Visual Principles Using Matplotlib and Seaborn. Provides users with the necessary foundations for building and understanding current state of the art visualizations. An additional aim is to provide users with an understanding of both the theory and techniques of various visualization paradigms. Finally, this series…

  • Updated Feb 23, 2021
  • Jupyter Notebook

DATA-X: m120 - Pandas - Introduction to Data Analysis Using Pandas. Pandas is a commonly used, yet powerful, software library written for Python that is built for expedient data manipulation and analysis. This notebook aims to introduce the syntax, data structures, and manipulation operations commonly seen in Pandas.

  • Updated Jul 16, 2020
  • Jupyter Notebook

DATA-X: m420 - Bread & Butter Deep Learning: Regression and Classification using TensorFlow v2 and Ludwig. This notebook covers advanced topics in machine learning. However, it does not require any prior knowledge in machine learning. The goal of this notebook is to teach a user how to deploy deep learning regression and classification models, u…

  • Updated Jul 22, 2020
  • Python

DATA-X: m410 - TensorFlow - Shallow Neural Networks; An Introduction to TensorFlow V.2. Tensorflow (TF) is an open-source library used for dataflow, differentiable programming, symbolic math, and machine learning applications such as deep learning neural networks. TF's flexible architecture allows for easy deployment across varied processing pla…

  • Updated Jul 24, 2020
  • Python

DATA-X: m110 - Numpy - Introduction to Numerical Analysis Using NumPy. These materials introduce developers and data scientists to numerical analysis and data manipulation using NumPy. NumPy is the numerical analysis backbone to several popular open source analysis and machine learning packages.

  • Updated Jul 17, 2020
  • Jupyter Notebook

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